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作 者:张屹 郝琪 陈蓓蕾 于海恩 范福兰 陈珍 Zhang Yi;Hao Qi;Chen Beilei;Yu Hanen;Fan Fulan;Chen Zhen(School of Educational Technology,Central China Normal University,Wuhan Hubei 430079;Faculty of Education Hubei University,Wuhan Hubei 430062;College of Information,Liaoning University,Shenyang Liaoning 110036;School of Education,South-Central University for Nationalities,Wuhan Hubei 430074)
机构地区:[1]华中师范大学教育信息技术学院,湖北武汉430079 [2]湖北大学教育学院,湖北武汉430062 [3]辽宁大学信息学院,辽宁沈阳110036 [4]中南民族大学教育学院,湖北武汉430074
出 处:《中国电化教育》2019年第1期106-115,共10页China Educational Technology
基 金:华中师范大学信息化应用自主科研项目"技术支持的形成性评价互动教学对大学生研究能力和投入度的影响研究--以<教育技术学研究方法>课程为例"(项目编号:CCNU18IT0311);The "Future Schools in 2030" program "The technology enhanced assessment to improve students’ deep learning in Smart Classroom"(项目编号:AICFE-IO-007)研究成果
摘 要:为了探究智慧教室环境下大学生课堂学习投入度的现状及影响因素,该文采用单组前后测实验研究法,以"教育技术学研究方法课"为例展开研究,并从学生自身因素、教师与同伴、智慧学习环境层面出发,利用多元回归分析方法探索大学生学习投入影响因素的作用机制。研究发现:(1)智慧教室环境下大学生的课堂学习投入情况较好,学生在行为、情感、认知层面的投入水平均有显著性提升;(2)智慧教室环境下免费师范生的学习投入水平高于非师范生,且在行为层面存在显著性差异;(3)技术支持下的师生交互行为、教师信息技术应用能力、技术接受度与认知负荷对学生行为投入存在显著性影响;自我效能感与师生交互行为对学生认知投入存在显著性影响;同时师生交互、生生交互行为、教学资源与平台对学生情感投入有显著性影响。The purpose of this study was to explore college students’ learning engagement and influencing factors in smart classroom. The research employs Single-group pretest-posttest experimental research, and takes "Educational Technology Research Method Course" as an example to implement outcome. Furthermore, the multiple regression analysis method is used to explore influencing factors from the perspective of students’ own factors, teachers-peers, and smart learning environment. The results indicate that:(1)College students are relatively positive in smart classroom, and the behavioral, emotional and cognitive engagement of post-surveys showed a significantly higher level than pre-surveys;(2)The level of learning engagement of free normal students is higher than that of non-normal students, and there are significant differences in behavior;(3)The teacher-student interaction under the technical support, the level of ICT competences for teachers, the technology acceptance and the cognitive load have significant influence on students’ behavior engagement;Self-efficacy and teacher-student interaction have significant effects on students’ cognitive engagement;In addition, teacher-student interaction, student-student interaction, and the teaching resources and platforms have a significant impact on students’ emotional engagement. Finally, these positive results efforts being made to offer several meaningful references for facilitating teaching and learning in smart classroom.
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